Gian Maria Campedelli

Machine Learning for Criminology and Crime Research (eBook, PDF)

At the Crossroads

• Format: PDF

Produktbeschreibung

Machine Learning for Criminology and Crime Research reviews the roots of the intersection between machine learning, Artificial Intelligence, and research on crime, examines the current state of the art in this area of scholarly inquiry, and discusses future perspectives that may emerge from this relationship.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 194
• Erscheinungstermin: 9. Juni 2022
• Englisch
• ISBN-13: 9781000596557
• Artikelnr.: 63794227

Autorenporträt

Gian Maria Campedelli is a Postdoctoral Research Fellow in Computational Sociology and Criminology at the University of Trento, Italy. In 2020, he earned a PhD in Criminology from Catholic University in Milan, Italy. From 2016 to 2019 he worked as a researcher at Transcrime, the Joint Research Center on Transnational Crime of Catholic University, University of Bologna, and University of Perugia. In 2018 he was also a visiting research scholar in the School of Computer Science at Carnegie Mellon University, in Pittsburgh, the United States. His research addresses the development and application of computational methods - especially machine learning and complex networks - to the study of criminal and social phenomena, with a specific focus on organized crime, violence, and terrorism.

Inhaltsangabe

Chapter 1: The "Novelty Narrative": An Unorthodox Introduction

Chapter 2: A Collective Journey: A Short Overview on Artificial Intelligence

Chapter 3: Criminology at the Crossroads? Computational Perspectives

Chapter 4: To Reframe and Reform: Increasing the Positive Social Impact of Algorithmic Applications in Research on Crime

Chapter 5: Causal Inference in Criminology and Crime Research and the Promises of Machine Learning

Chapter 6: Concluding Remarks

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Chapter 1: The "Novelty Narrative": An Unorthodox Introduction
Chapter 2: A Collective Journey: A Short Overview on Artificial
Intelligence
Chapter 3: Criminology at the Crossroads? Computational Perspectives
Chapter 4: To Reframe and Reform: Increasing the Positive Social Impact of
Algorithmic Applications in Research on Crime
Chapter 5: Causal Inference in Criminology and Crime Research and the
Promises of Machine Learning
Chapter 6: Concluding Remarks